Learning from Data Streams in Dynamic Environments - Moamar Sayed-Mouchaweh
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This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-s ... Pilns apraksts
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Aprašymas
This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.
Vairāk informācijas
| Autors | Moamar Sayed-Mouchaweh |
|---|---|
| Izdevējs | Springer Nature Switzerland |
| Series | SpringerBriefs in Applied Sciences and Technology |
| Izlaides gads | 2015 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783319256658 |